1 code implementation • 8 Mar 2024 • Xavier Bou, Gabriele Facciolo, Rafael Grompone von Gioi, Jean-Michel Morel, Thibaud Ehret
Moreover, we study the performance of both visual and image-text features, namely DINOv2 and CLIP, including two CLIP models specifically tailored for remote sensing applications.
no code implementations • 6 Mar 2024 • Yu Guo, Axel Davy, Gabriele Facciolo, Jean-Michel Morel, Qiyu Jin
In this letter, we propose a solution to both issues by combining a nonlocal algorithm with a lightweight residual CNN.
no code implementations • 9 Jul 2023 • Xavier Bou, Aitor Artola, Thibaud Ehret, Gabriele Facciolo, Jean-Michel Morel, Rafael Grompone von Gioi
Experimental results reveal that the proposed a-contrario validation is able to largely reduce the number of false alarms at both pixel and object levels.
no code implementations • 4 Jul 2023 • Franco Marchesoni-Acland, Jean-Michel Morel, Josselin Kherroubi, Gabriele Facciolo
The problem is framed as the full annotation of a binary classification dataset with the minimal number of yes/no questions when a predictor is available.
1 code implementation • 25 May 2023 • Adrien Courtois, Damien Scieur, Jean-Michel Morel, Pablo Arias, Thomas Eboli
We propose SING (StabIlized and Normalized Gradient), a plug-and-play technique that improves the stability and generalization of the Adam(W) optimizer.
no code implementations • 25 May 2023 • Thomas Eboli, Jean-Michel Morel, Gabriele Facciolo
Blurry images usually exhibit similar blur at various locations across the image domain, a property barely captured in nowadays blind deblurring neural networks.
no code implementations • 27 Dec 2022 • Bruno Galerne, Lara Raad, José Lezama, Jean-Michel Morel
Neural style transfer is a deep learning technique that produces an unprecedentedly rich style transfer from a style image to a content image and is particularly impressive when it comes to transferring style from a painting to an image.
no code implementations • 7 Nov 2022 • Adrien Courtois, Jean-Michel Morel, Pablo Arias
In particular, what are the interpolation capabilities of trained neural networks?
no code implementations • 1 Aug 2022 • Thomas Eboli, Jean-Michel Morel, Gabriele Facciolo
The optics of any camera degrades the sharpness of photographs, which is a key visual quality criterion.
1 code implementation • 23 Apr 2022 • Adrien Courtois, Jean-Michel Morel, Pablo Arias
It is therefore impossible to know what cues a given neural structure is taking advantage of in such data.
no code implementations • 4 May 2021 • Quentin Bammey, Tina Nikoukhah, Marina Gardella, Rafael Grompone, Miguel Colom, Jean-Michel Morel
With the aim of evaluating image forensics tools, we propose a methodology to create forgeries traces, leaving intact the semantics of the image.
2 code implementations • IEEE International Geoscience and Remote Sensing Symposium IGARSS 2021 • Roland Akiki, Roger Marí, Carlo de Franchis, Jean-Michel Morel, Gabriele Facciolo
The Rational Polynomial Camera (RPC) model can be used to describe a variety of image acquisition systems in remote sensing, notably optical and Synthetic Aperture Radar (SAR) sensors.
no code implementations • 14 Sep 2020 • Yu Guo, Qiyu Jin, Gabriele Facciolo, Tieyong Zeng, Jean-Michel Morel
Image demosaicking and denoising are the first two key steps of the color image production pipeline.
no code implementations • 24 Apr 2020 • Qiyu Jin, Gabriele Facciolo, Jean-Michel Morel
In this paper, we review the main variants of these strategies and carry-out an extensive evaluation to find the best way to reconstruct full color images from a noisy mosaic.
no code implementations • 25 Apr 2019 • Axel Davy, Thibaud Ehret, Jean-Michel Morel, Mauricio Delbracio
Anomaly detectors address the difficult problem of detecting automatically exceptions in an arbitrary background image.
2 code implementations • 30 Nov 2018 • Axel Davy, Thibaud Ehret, Jean-Michel Morel, Pablo Arias, Gabriele Facciolo
To the best of our knowledge, this is the first successful application of a CNN to video denoising.
1 code implementation • CVPR 2019 • Thibaud Ehret, Axel Davy, Jean-Michel Morel, Gabriele Facciolo, Pablo Arias
Modeling the processing chain that has produced a video is a difficult reverse engineering task, even when the camera is available.
no code implementations • 28 Aug 2018 • Charles Hessel, Jean-Michel Morel
For each of these artifacts we design a test-pattern and its attached measurement formula.
no code implementations • 7 Aug 2018 • Thibaud Ehret, Axel Davy, Jean-Michel Morel, Mauricio Delbracio
We review the broad variety of methods that have been proposed for anomaly detection in images.
no code implementations • 25 May 2018 • José Lezama, Samy Blusseau, Jean-Michel Morel, Gregory Randall, Rafael Grompone von Gioi
Using a computational quantitative version of the non-accidentalness principle, we raise the possibility that the psychophysical and the (older) gestaltist setups, both applicable on dot or Gabor patterns, find a useful complement in a Turing test.
no code implementations • 22 Jul 2017 • Lara Raad, Axel Davy, Agnès Desolneux, Jean-Michel Morel
The two main approaches are statistics-based methods and patch re-arrangement methods.
no code implementations • 19 Jan 2017 • Martin Rais, Gabriele Facciolo, Enric Meinhardt-Llopis, Jean-Michel Morel, Antoni Buades, Bartomeu Coll
This yields RANSAAC, a framework that improves systematically over RANSAC and its state-of-the-art variants by statistically aggregating hypotheses.
no code implementations • 18 Mar 2016 • Boshra Rajaei, Rafael Grompone von Gioi, Jean-Michel Morel
In this paper, we reconsider the early computer vision bottom-up program, according to which higher level features (geometric structures) in an image could be built up recursively from elementary features by simple grouping principles coming from Gestalt theory.
no code implementations • 26 Nov 2015 • Ives Rey-Otero, Jean-Michel Morel, Mauricio Delbracio
In practice, however, scale invariance may be weakened by various sources of error inherent to the SIFT implementation affecting the stability and accuracy of keypoint detection.
no code implementations • 8 Sep 2014 • Ives Rey-Otero, Mauricio Delbracio, Jean-Michel Morel
We apply this variant to revisit the popular benchmark by Mikolajczyk et al., on classic and new feature detectors.
no code implementations • CVPR 2014 • Jose Lezama, Rafael Grompone von Gioi, Gregory Randall, Jean-Michel Morel
We present a novel method for automatic vanishing point detection based on primal and dual point alignment detection.